AI system ProMUSE cuts Alzheimer's diagnosis costs with adaptive imaging

Researchers have developed ProMUSE, a novel AI system designed to improve the early diagnosis of Alzheimer's disease by adaptively incorporating multi-modal data. This system initially uses low-cost clinical assessments and quantifies diagnostic uncertainty. If the uncertainty is high, ProMUSE progressively integrates more expensive data like MRI and PET scans, using Dempster-Shafer theory to fuse information and reduce reliance on costly imaging. Experiments on benchmark datasets show ProMUSE can achieve comparable accuracy to full-modality approaches while significantly reducing the need for MRI/PET scans, offering a more cost-effective solution for widespread screening. AI

IMPACT Enables more cost-effective and widespread early diagnosis of Alzheimer's disease by reducing reliance on expensive imaging techniques.

RANK_REASON The cluster describes a new research paper detailing an AI model for medical diagnosis. [lever_c_demoted from research: ic=1 ai=1.0]

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• Alzheimer's disease
• Alzheimer's Disease Neuroimaging Initiative
• Dempster–Shafer theory
• Dirichlet
• magnetic resonance imaging
• OASIS
• positron emission tomography

• paper
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